[1] Darehshiri, A., Panji, M., & Mokhtari, A. R. (2015). Identifying geochemical anomalies associated with Cu mineralization in stream sediment samples in Gharachaman area, northwest of Iran. Journal of African Earth Sciences, 110, 92-99.
[2] Momeni, S., Shahrokhi, S. V., Afzal, P., Sadeghi, B., Farhadinejad, T., & Nikzad, M. R. (2016). Delineation of the Cr mineralization based on the stream sediment data utilizing fractal modeling and factor analysis in the Khoy 1: 100,000 sheet, NW Iran. Bulletin of the Mineral Research and Exploration, 152(152), 143-151.
[3] Afzal, P., Farhadi, S., Boveiri Konari, M., Shamseddin Meigooni, M., & Daneshvar Saein, L. (2022). Geochemical anomaly detection in the Irankuh District using Hybrid Machine learning technique and fractal modeling. Geopersia, 12(1), 191-199.
[4] Farhadi, S., Afzal, P., Boveiri Konari, M., Daneshvar Saein, L., & Sadeghi, B. (2022). Combination of Machine Learning Algorithms with Concentration-Area Fractal Method for Soil Geochemical Anomaly Detection in Sediment-Hosted Irankuh Pb-Zn Deposit, Central Iran. Minerals, 12(6), 689.
[5] Torshizian, H., Afzal, P., Rahbar, K., Yasrebi, A. B., Wetherelt, A., & Fyzollahhi, N. (2021). Application of modified wavelet and fractal modeling for detection of geochemical anomaly. Geochemistry, 81(4), 125800.
[6] Ghannadpour, S. S., & Hezarkhani, A. (2022). A new method for determining geochemical anomalies: UN and UA fractal models. International Journal of Mining and Geo-Engineering, 56(2), 181-190.
[7] Zadmehr, F., & Shahrokhi, S. V. (2019). Separation of geochemical anomalies by concentration-area and concentration-number methods in the Saqez 1: 100,000 sheet, Kurdistan. Iranian Journal of Earth Sciences, 11(3), 196-204.
[8] Ziaii, M., Pouyan, A. A., & Ziaei, M. (2009). Neuro-fuzzy modelling in mining geochemistry: identification of geochemical anomalies. Journal of Geochemical Exploration, 100(1), 25-36.
[9] Yousefi, S.; Doulati Ardejani, F.; Ziaii, Karamoozian, M.; 2015; “The speciation of cobalt and nickel at mine waste dump using improved correlation analysis: a case study of Sarcheshmeh copper mine”.Environment, development and sustainability, 17(5),pp.1065-1084.
[10] Shahrestani, S., Mokhtari, A. R., & Alipour-Asll, M. (2019). Assessment of Estimated Bedrock and Stream Sediment Geochemical Backgrounds in Catchment Basin Analysis. Natural Resources Research, 28, 1071-1087.
[11] Wu, R., Chen, J., Zhao, J., Chen, J., & Chen, S. (2020). Identifying geochemical anomalies associated with gold mineralization using factor analysis and spectrum–area multifractal model in Laowan District, Qinling-Dabie Metallogenic Belt, Central China. Minerals, 10(3), 229.
[12] Satyanarayanan, M., Eswaramoorthi, S., Subramanian, S., & Periakali, P. (2017). Factor analysis of rock, soil and water geochemical data from Salem magnesite mines and surrounding area, Salem, southern India. Applied Water Science, 7, 2607-2616.
[13] Valsangkar, A. B., Karisiddaiah, S. M., & Ambre, N. V. (1992). Geochemistry, factor analysis and clay mineral distribution of the sediments and relationship with the associated ferromanganese nodules from the SW Carlsberg Ridge.
[14] Uusikorpi, J. (2020). Factor analysis of a large geochemical exploration data set: example from Kalba gold belt, eastern Kazakhstan.
[15] Reimann, C., Filzmoser, P., & Garrett, R.G. (2002). Factor analysis applied to regional geochemical data: problems and possibilities. Applied Geochemistry, 17, 185-206.
[16] Sun, X., Deng, J., Gong, Q., Wang, Q., Yang, L., & Zhao, Z. (2009). Kohonen neural network and factor analysis based approach to geochemical data pattern recognition. Journal of Geochemical Exploration, 103(1), 6-16.
[17] Van Helvoort, P. J., Filzmoser, P., & van Gaans, P. F. (2005). Sequential factor analysis as a new approach to multivariate analysis of heterogeneous geochemical datasets: an application to a bulk chemical characterization of fluvial deposits (Rhine–Meuse delta, The Netherlands). Applied geochemistry, 20(12), 2233-2251.
[18] Sun, X., Deng, J., Gong, Q., Wang, Q., Yang, L., & Zhao, Z. (2009). Kohonen neural network and factor analysis based approach to geochemical data pattern recognition. Journal of Geochemical Exploration, 103(1), 6-16.
[19] Ayoobi, I., Shamsipour Dehkordi, R., & Shiva, M. (2013). Anomaly recognition in stream sediment geochemical exploration using factor analysis in Mesgaran area of Birjand, eastern Iran. Journal of Economic Geology, 5(1), 105-115 (In Persian).
[20] Tripathi, V. S. (1979). Factor analysis in geochemical exploration. Journl of Geochemical Exploration, 11(3), 263-275.
[21] Helba, H. A., El-Makky, A. M., & Khalil, K. I. (2021). Application of the CN fractal model, factor analysis and geochemical mineralization probability index (GMPI) for delineating geochemical anomalies related to a Mn-Fe deposit and associated Cu mineralization in west-central Sinai, Egypt. Geochemistry: Exploration, Environment, Analysis, 21(3).
[22] Yousefi, M., Kamkar-Rouhani, A., & Carranza, E. J. M. (2014). Application of staged factor analysis and logistic function to create a fuzzy stream sediment geochemical evidence layer for mineral prospectivity mapping.
[23] M. Daviran, R. Ghavami, A. Maghsoudi, and R. Ghezelbash, Identification of Hydrothermal alteration zones using ASTER data in northern parts of Doruneh fault within the Feizabad sheet. 2017 (In Persian).
[24] Behroozi A (1987) Geological map of Iran 1: 100,000 series, Feizabad.Geological Survey of Iran, Tehran (In Persian(.
[25] Yousefi, M., Kamkar-Rouhani, A., & Alipoor, M. (2014). Increasing the Exploration Success and Intensify of Stream Sediment Geochemical Halos Using Recognizing and Omitting the Non-Predictive Factors, Case Studies: Fluorite and Copper Mineralization. Scientific Quarterly Journal of Geosciences, 24(93), 85-92. doi: 10.22071/gsj.2014.43531 (In Persian).
[26] Hassani Pak, A., A., (2016). Geochemical exploration, 9th edition, University of tehran press, (In Persian.(
[27] Cox, D.R., Snell, E.J., (1989). Analysis of Binary Data, 2nd ed. Chapman and Hall, London
[28] Yousefi, M., Kamkar-Rouhani, A., & Carranza, E. J. M. (2012). Geochemical mineralization probability index (GMPI): a new approach to generate enhanced stream sediment geochemical evidential map for increasing probability of success in mineral potential mapping. Journal of Geochemical Exploration, 115, 24-35.
[29] Yousefi, M., & Carranza, E. J. M. (2015). Prediction–area (P–A) plot and C–A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling. Computers & Geosciences, 79, 69-81.
[30] Brown, W. M., Gedeon, T. D., & Groves, D. I. (2003). Use of noise to augment training data: a neural network method of mineral–potential mapping in regions of limited known deposit examples. Natural Resources Research, 12, 141-152.